Social Weather Stations Survey: 2013 Fourth Quarter
Bibliographic record
Abstract
Area in Philippines (1); class of dwelling (1); household facilities (12); looking for employment (6); occupation (1); wage increase in past three months (1); type of employment (1); normal working hours per day in past week (3); minimum wage (1); live abroad (1); finding a job (2); working abroad (3); self-rated poverty (4); food poverty and expenses each month (4); hunger in last three months (2); typhoon Yolanda (7); aftermath of typhoons (52); primary language used at home (1); job availability (2); video or computer games (1); feelings after interview (2); quality of life trend over last twelve months (2); economy of the Philippines (3); proud to be a Filipino (1); happiness and life satisfaction (1); news events in past three months (15); President Benigno Aquino III (1); next President of the Philippines (5); job approval of government officials (25); job approval of government institutions (6); performance ratings of present national administration on specific issues (13); satisfaction with typhoon relief efforts (12); confidence in government's ability to handle typhoon (6); recovery from typhoon Yolanda (3); looting (4); weather forecasts and warnings (6); Disbursement Assistance Program (stimulus program) (3); Priority Development Assistance Fund (2); Janet Lim Napoles scandal (2); helpful government agencies for Filipinos living abroad (2); dispute with China over West Philippine Sea (8); trust in public figures (8); awareness and trust of different countries (6); K to 12 Basic Education Program (extra years of high school) (2); shortage of classrooms (1); teacher quality (1); education (2); Philhealth (health insurance coverage program) (12); HMO/private insurance (1); crime (6); Maguindanao Massacre (2); ATM/debit cards (4); purchases and bills (8); Christmas (2); New Year's (1); relationships (4).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".